Spaces:
Sleeping
Sleeping
Update app.py
Browse files
app.py
CHANGED
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@@ -155,8 +155,89 @@ def archive_current_container(database_name, container_name, client):
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except Exception as e:
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return f"An error occurred while archiving data: {str(e)} π’"
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def search_glossary(query):
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# π΅οΈββοΈ Searching the glossary for: query
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all_results = ""
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st.markdown(f"- {query}")
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@@ -176,7 +257,6 @@ def search_glossary(query):
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#llm_model_picked Literal['mistralai/Mixtral-8x7B-Instruct-v0.1', 'mistralai/Mistral-7B-Instruct-v0.2', 'google/gemma-7b-it', 'None'] Default: "mistralai/Mistral-7B-Instruct-v0.2"
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-
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client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
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result = client.predict(
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prompt=query,
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@@ -184,7 +264,6 @@ def search_glossary(query):
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stream_outputs=True,
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api_name="/ask_llm"
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)
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-
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st.write('π Run of Multi-Agent System Paper Summary Spec is Complete')
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st.markdown(response2)
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@@ -197,9 +276,12 @@ def search_glossary(query):
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"mistralai/Mixtral-8x7B-Instruct-v0.1", # LLM Model Dropdown component
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api_name="/update_with_rag_md"
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)
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return responseall
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# π Function to process text input
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@@ -465,6 +547,7 @@ def main():
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st.error(message)
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except json.JSONDecodeError as e:
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st.error(f"Invalid JSON: {str(e)} π«")
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elif selected_view == 'Show as Edit and Save':
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# βοΈ Show as Edit and Save in columns
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st.markdown("#### Edit the document fields below:")
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@@ -494,6 +577,7 @@ def main():
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st.error(message)
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except json.JSONDecodeError as e:
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st.error(f"Invalid JSON: {str(e)} π«")
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elif selected_view == 'Clone Document':
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# 𧬠Clone Document per record
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st.markdown("#### Clone a document:")
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@@ -525,6 +609,7 @@ def main():
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st.error(message)
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except json.JSONDecodeError as e:
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st.error(f"Invalid JSON: {str(e)} π«")
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elif selected_view == 'New Record':
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# π New Record
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st.markdown("#### Create a new document:")
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@@ -544,6 +629,7 @@ def main():
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st.error(message)
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except json.JSONDecodeError as e:
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st.error(f"Invalid JSON: {str(e)} π«")
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else:
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st.sidebar.info("No documents found in this container. π")
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except Exception as e:
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return f"An error occurred while archiving data: {str(e)} π’"
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+
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# Helper to extract hyperlinks
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def extract_hyperlinks(responses):
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hyperlinks = []
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for response in responses:
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parsed_response = json.loads(response)
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links = [value for key, value in parsed_response.items() if isinstance(value, str) and value.startswith("http")]
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hyperlinks.extend(links)
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return hyperlinks
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# Helper to format text with line numbers
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def format_with_line_numbers(text):
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lines = text.splitlines()
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formatted_text = '\n'.join(f"{i+1}: {line}" for i, line in enumerate(lines))
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return formatted_text
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# Save responses to Cosmos DB
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def save_to_cosmos_db(query, response1, response2):
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cosmos_container = st.session_state.get("cosmos_container")
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if cosmos_container:
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record = {
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"query": query,
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"response1": json.loads(response1),
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"response2": json.loads(response2)
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}
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try:
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cosmos_container.create_item(body=record)
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st.success(f"Record saved successfully with ID: {record['id']}")
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except exceptions.CosmosHttpResponseError as e:
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st.error(f"Error saving record to Cosmos DB: {e}")
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else:
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st.error("Cosmos DB is not initialized.")
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# Add dropdowns for model and database choices
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def search_glossary(query):
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st.markdown(f"### π Search Glossary for: `{query}`")
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# Dropdown for model selection
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model_options = ['mistralai/Mixtral-8x7B-Instruct-v0.1', 'mistralai/Mistral-7B-Instruct-v0.2', 'google/gemma-7b-it', 'None']
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model_choice = st.selectbox('π§ Select LLM Model', options=model_options, index=1)
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# Dropdown for database selection
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database_options = ['Semantic Search', 'Arxiv Search - Latest - (EXPERIMENTAL)']
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database_choice = st.selectbox('π Select Database', options=database_options, index=0)
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# Run Button with Emoji
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if st.button("π Run"):
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# ArXiv searcher - Paper Summary & Ask LLM
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client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
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response1 = client.predict(
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message=query,
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llm_results_use=5,
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database_choice=database_choice,
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llm_model_picked=model_choice,
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api_name="/update_with_rag_md"
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)
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response2 = client.predict(
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prompt=query,
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llm_model_picked=model_choice,
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stream_outputs=True,
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api_name="/ask_llm"
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)
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# Aggregate hyperlinks and show with emojis
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hyperlinks = extract_hyperlinks([response1, response2])
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st.markdown("### π Aggregated Hyperlinks")
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for link in hyperlinks:
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st.markdown(f"π [{link}]({link})")
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# Show responses in a code format with line numbers
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st.markdown("### π Response Outputs with Line Numbers")
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st.code(f"Response 1: \n{format_with_line_numbers(response1)}\n\nResponse 2: \n{format_with_line_numbers(response2)}", language="json")
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# Save both responses to Cosmos DB
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save_to_cosmos_db(query, response1, response2)
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# π Search Glossary function
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def search_glossaryv1(query):
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# π΅οΈββοΈ Searching the glossary for: query
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all_results = ""
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st.markdown(f"- {query}")
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#llm_model_picked Literal['mistralai/Mixtral-8x7B-Instruct-v0.1', 'mistralai/Mistral-7B-Instruct-v0.2', 'google/gemma-7b-it', 'None'] Default: "mistralai/Mistral-7B-Instruct-v0.2"
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client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
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result = client.predict(
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prompt=query,
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stream_outputs=True,
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api_name="/ask_llm"
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)
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st.write('π Run of Multi-Agent System Paper Summary Spec is Complete')
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st.markdown(response2)
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"mistralai/Mixtral-8x7B-Instruct-v0.1", # LLM Model Dropdown component
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api_name="/update_with_rag_md"
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)
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#st.write('π Run of Multi-Agent System Paper References is Complete')
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#responseall = response2 + response1[0] + response1[1]
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#st.markdown(responseall)
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return responseall
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# π Function to process text input
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st.error(message)
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except json.JSONDecodeError as e:
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st.error(f"Invalid JSON: {str(e)} π«")
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elif selected_view == 'Show as Edit and Save':
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# βοΈ Show as Edit and Save in columns
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st.markdown("#### Edit the document fields below:")
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st.error(message)
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except json.JSONDecodeError as e:
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st.error(f"Invalid JSON: {str(e)} π«")
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elif selected_view == 'Clone Document':
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# 𧬠Clone Document per record
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st.markdown("#### Clone a document:")
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st.error(message)
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except json.JSONDecodeError as e:
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st.error(f"Invalid JSON: {str(e)} π«")
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elif selected_view == 'New Record':
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# π New Record
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st.markdown("#### Create a new document:")
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st.error(message)
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except json.JSONDecodeError as e:
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st.error(f"Invalid JSON: {str(e)} π«")
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else:
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st.sidebar.info("No documents found in this container. π")
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